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For designing new products or developing new specifications, the reliability performance of systems and components experienced by the customer provides invaluable information for the engineer. This information, not only provides for the visibility of reliability requirements, but also an awareness of potential degradation of the systems and components during its life cycle. In this paper, a method is presented for predicting vehicle system and component reliability from vehicle fleet repair data. This method combines sampling stratification, computer data analysis and statistical modeling techniques into a reliability analysis procedure to provide reliability prediction. Specifically, published vehicle fleet data was used to provide the basis for predicting the vehicle system and component reliability at any mileage level.

The reliability of an electronic sensor in the automotive applications is assessed using data from Fleet Test and proving ground Vehicle Endurance test. These nonfailure data are multiply censored at different mileage. Reliability analysis of data with no failure is rarely discussed in most reliability literature. This paper applies the Weibull maximum likelihood analysis based on known values of the Weibull shape parameter to extract useful reliability information. The well-known Weibayes and Weibest methods are subsets of the discussed approach. The sensitivity of the change of reliability levels over a range of Weibull shape parameter values is also examined in our case. The Huang-Porter (1991) approach of obtaining a reliability lower bound regardless of the Weibull shape parameter values is also applied and its potential of practical application is discussed. Practical limitations of all methods are discussed.

A few years ago, electric vehicles (EVs) were considered to be objects of the distant future … technology that was still in its infancy, not yet ready and for those outside the “high pollution” areas probably not even worth the expenditure. But the present day scenario has changed dramatically. In the United States of America, several states are following California's lead and the need for the operating fleets to commit to purchase of Zero Emission vehicles (ZEVs) is becoming a requirement. In order to make the technology available to the utilities … as well as the public, state of the art, affordable batteries are essential for making EVs a reality and an effective means of transportation.

TFC/IW, total fuel consumption divided by inertia (test) weight is a useful concept in analyzing the total or composite fuel economy generated in thousands of tests using the carbon balance technique in EPA Federal Test Procedure and Highway Driving Cycle. TFC/IW is a measure of drive train efficiency that requires no additional complicating assumptions. It is applicable to one test or a fleet representing many tests.